Vibe Engineering with AI Coding Agents
A hands-on course that takes you from “what even is vibe coding?” to shipping real apps with an AI agent — and understanding exactly what is happening under the hood while it does. Taught at SMIT by Muhammad Uzair Khan.
Your class-by-class map
Read straight through, or jump to any topic. Every page stands on its own and links to the next.
See the magic, then name it
Generate a 3D game from a sentence, then build the mental map: the Missing Manual, vibe coding vs. agentic engineering, the eight stages of AI adoption, and where the money goes.
What’s under the hood
Tokens, memory, reasoning, tools and loops — the four tricks that turn autocomplete into an agent. Then context engineering, agents.md, and how professional workflows have evolved.
Build for real
Install the tools, write a great agents.md, and drive Cursor in YOLO mode to build a working Kanban board — planning, generating, testing, and iterating with feedback.
Choose your model, then YOLO
Pick the right model, learn the five “be the boss” principles, set up OpenRouter, and vibe-code a portfolio site with an AI digital twin — then review it with a second model.
Meet Claude Code — and its rivals
Install Claude Code in VS Code, learn the CLI — /init, /context, running tests — then run free and cheap models through OpenCode, AMP, OpenRouter and local Ollama.
See it work — then understand what you saw
Instant gratification first, theory second. You’ll feel the power before you dissect it.
Welcome & your first build →
Meet Cursor and generate a playable 3D shooter from a single prompt — no code written.
The Missing Manual →
Why this course exists, who it’s for, vibe coding vs. agentic engineering, and the three surfaces.
Eight stages & the cost talk →
Steve Yegge’s ladder from ChatGPT to agent orchestration — and an honest word about AI spend.
The one heavy-theory day — and worth every minute
Understand the mechanics and every later trick makes sense. Experts: feel free to skim.
How LLMs actually work →
Tokens, the illusion of memory, reasoning, tools and loops — and a precise definition of an agent.
Context engineering →
System prompts, the context window, compacting, and the all-important agents.md file.
Workflows & choosing a model →
From micromanagement to Ralph Loops and swarms — plus reading artificialanalysis.ai.
Less talking, more doing
Tour the tools, then build and iterate on a genuine app with an agent at your side.
Tools, setup & agents.md →
Cursor, Copilot, Codex, Antigravity — install Node, clone the repo, and read a real agents.md line by line.
Build the Kanban app →
Plan mode, YOLO mode, watching the agent loop, and sharpening it with targeted feedback.
Do it yourself →
Jump straight to the hands-on lab and build it with your own hands.
Choose your model — then really build
Break the rules on purpose with a real YOLO build, then come back and own every line.
Choosing your model →
Two decisions, not one: the tool vs. the model. Fast frontier vs. top frontier — and when it’s safe to YOLO.
Be the boss →
The five principles for successful vibe coding — spec, start simple, iterate, challenge, handle frustration.
Responsible YOLO →
Two honest counterpoints, the “own the code” mantra, and setting up an OpenRouter API key.
The YOLO build →
Ship a Next.js portfolio site with an AI digital twin — then tutorial it and review it with a second model.
Karpathy & the MVP →
The tweets that named vibe coding, the workflow shift, and a balanced mindset for building for real.
Claude Code — and how to run any model
Install the tool that started it all, master the CLI, then explore every free and cheap alternative.
The rise of Claude Code →
Its history from a 2024 side project to Opus 4.5 — plus pricing, and installing it inside VS Code.
CLI: init, context & testing →
/login, /init and /context — then let Claude run your whole test suite.
OpenCode & free models →
Run genuinely free models like GLM 4.7, and connect any provider you like.
AMP, OpenRouter & Ollama →
Ad-supported credits, Claude Code pointed at OpenRouter, and models running locally.
Roll up your sleeves
Two guided, self-paced labs. No grade, no pressure — just reps. Both work on free tiers.
One prompt, one app →
Generate a working app from a single sentence, improve it with follow-ups, then run the same prompt twice and watch it diverge. Your first taste of non-determinism.
Write agents.md, build in YOLO →
Author a real agents.md, clone the starter, and drive Cursor through plan → build → test → feedback to ship a drag-and-drop Kanban board.
✓ By the end of these classes you can…
- Generate a working app from a single prompt and improve it through conversation.
- Explain what an LLM is doing — tokens, memory, reasoning, tools, loops — and define an “agent” precisely.
- Write a tight, effective
agents.mdand understand how the context window shapes results. - Choose deliberately between tools and models, and know when it’s safe to YOLO.
- Drive an AI-native IDE (Cursor) in plan and YOLO modes to build, review, and debug real applications.
- Ship a portfolio site with an AI digital twin via OpenRouter — and own every line of it.
- Install and drive Claude Code from the terminal — and run free or cheap models through OpenCode, AMP, OpenRouter and Ollama.
Everything here works for total beginners and seasoned engineers alike. If a section is obvious to you, put it on 2× and skim — there’s something for everyone. Use the ☾ button up top to switch between light and dark, and the left sidebar to jump around.